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This research aims to evaluate how different prompting strategies influence the performance of LLM-controlled robots in production systems.

May 15, 2026Open Access

LLM-Based Multimodal Prompting for Adaptive Robot Control in Production Systems

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This research aims to evaluate how different prompting strategies influence the performance of LLM-controlled robots in production systems.
Laboratory demonstrator setup to test LLM-controlled pick-and-place robot.
Comparison of zero-shot versus multimodal few-shot prompting strategies using visual examples.
Dedicated evaluation model utilizing metrics for plan success, action success, and plan optimality.
Multimodal few-shot prompting improves planning accuracy by a significant margin.
Robustness and adaptability of the LLM-controlled robot increase with multimodal prompting compared to zero-shot.
Quantitative metrics show enhanced performance in real-world task execution.

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Randomized trial compares multimodal prompting strategies impacting robot control in production systems, indicating enhanced adaptability.

Koch et al. (2026) studied this question.

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Randomized trial compares multimodal prompting strategies impacting robot control in production systems, indicating enhanced adaptability.